Beschreibung: Although microcosm experiments are a frequent tool used to address fundamental ecological questions, there has been no quantitative assessment of the reproducibility of any microcosm experiment. This dataset contains the response variables measured in a multi-laboratory microcosm study in which the same microcosm experiment was repeated in 14 laboratories across Europe. All laboratories simultaneously run a simple microcosm experiment using grass (Brachypodium distachyon L.) monocultures and grass and legume (Medicago truncatula Gaertn.) mixtures. All twelve variables were then used to calculate the effect of the presence of nitrogen-fixing legume on the grass-legume mixtures (i.e. the net legume effect). The project tested a controversial hypotheses postulating that stringent levels of environmental and biotic standardization in experimental studies reduces reproducibility by amplifying impacts of lab-specific environmental factors not accounted for in the experimental design. This implies that the deliberate introduction of controlled systematic variability (CSV) in experimental designs can increase reproducibility. To test this hypothesis, each laboratory followed the same experimental protocol and introduced environmental and genotypic controlled systematic variability (CSV) within and among replicated microcosms established in either growth chambers (with stringent control of environmental conditions) or glasshouses (with more variable environmental conditions). Data were used to test the extent to which the effect size of the net legume effect varied with the CSV treatment and to estimate the number of laboratories that produced results that can be considered reproducible.

Beschreibung: Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity–ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that humankind depends upon. In this chapter, we argue that a multitrophic perspective of biotic interactions in random and non-random biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary ecology, community ecology, and ecosystem ecology in future BEF research will be key to refine conservation targets and develop sustainable management strategies.